1. What do I know?
3.2.3 · 35–55 minutes · reflect, test, discuss, review
1. What do I know?
Explore this area: What do I know?
1. What do I know?
Likierman elements: Knowledge and experience + Awareness
Recognise the boundaries of your understanding and read the situation before forming a view.
Relevant experience, not familiarity
Knowing a product as a customer can help you ask useful questions. It does not automatically supply experience of its financing, cash generation or competitive position. Record what you know directly, what you infer from an analogy and what requires someone else’s expertise. A beginner can exercise judgement by recognising a gap, checking a source or choosing to wait.
Read the situation
Awareness includes how a question is framed, who is speaking, what has changed and what is being left unsaid. Ask whether a past example really fits this business, market and time. Notice pressure for a quick answer and the difference between a promotional presentation and verified evidence. Awareness also matters in the other two areas; these groups are a learning aid, not sealed compartments.
Area workshop · What do I know?
DailyCup’s founder cites a successful city-centre outlet as evidence for a new school-area site. You know the brand as a customer. Separate relevant knowledge, an untested analogy and a context difference. Name one evidence gap, who could help and a proportionate next step.
Make your own attempt before opening feedback.
Area workshop model response
Customer experience may inform product questions. It does not establish comparable rents, weekday demand, term-time seasonality or cash generation. Investigate paid transactions, catchment and costs at genuinely comparable outlets, checking selection and definitions. Seek operational and accounting expertise without treating a confident specialist as infallible. Waiting for this information can be justified.
Private reflection: Where did familiarity or a first number make me feel I knew more than I could support? What did I notice only after slowing down?
Likierman · six elements explained by London Business School
Public LBS explanation checked on 1 November 2026. Six elements are attributed to Sir Andrew Likierman; the three-area grouping and investing exercises are On Judgement adaptations, not his published model or an endorsement.
Andrew Likierman · Judgement at Work: Making Better Choices
Publisher book page. The full book has not been reviewed; teaching uses the publicly explained six-element framework with original examples.
What you will learn
- Distinguish confidence, accuracy and precision.
- Use reference cases and probability statements carefully.
- Review calibration across a set of judgements.
3.2 · The Human Side
The Human Side
The Human Side · the work you will do
- 1What do I know?
- 2What influences me?
- 3How do I act?
- 4Record and review
Before you begin
Your first decision
You have spent two evenings researching DailyCup. Someone in your club has watched a two-minute video and sounds completely certain. Who would you trust? Before you answer, write down what would make either view worth listening to.
Record your first answer before continuing.
Video coming soon · about 3 minutes
When Confidence Outruns Evidence
Use the narration below while the recording is being made, then try the decisions in this lesson.
Read the full narration
You have spent two evenings researching DailyCup. Someone in your club has watched a two-minute video and sounds completely certain. Who would you trust? Before you answer, write down what would make either view worth listening to.
In this lesson, notice what affects your own judgement. You do not need to invest real money or share personal financial information.
You can know a business well and still be wrong about its future. You can also be right while sounding unsure. Start by separating three things: how confident you feel, how accurate your forecast turns out to be, and how narrow a range you give. A confident pitch should make you ask better questions, rather than stop asking them.
You know why DailyCup’s next cafe could succeed. What happened when similar businesses opened similar sites? Look for comparable launches, including the ones that struggled. This comparison group is your reference class. Its base rate gives you a starting point to challenge your story. It will not tell you the answer if the businesses or conditions are materially different.
“It will probably work” is difficult to learn from. Try: “I give the new site a 70% chance of reaching the stated sales target by December.” Define the target and the source that will settle it. A 70% forecast allows a 30% chance of failure. You need a series of forecasts to see whether your confidence is usually well judged.
“DailyCup is worth somewhere between nothing and £10 million” covers plenty of possibilities but barely helps a decision. Explain the assumptions behind the low and high values. Then identify the information that would narrow the range. Your aim is useful honesty about uncertainty. It is not to sound certain, or to make a forecast so vague that you can never be wrong.
Pause for the worked example and the choices. Use the feedback to improve the explanation, then apply it to the fictional case. Keep your first view as well as any revision.
Think about your first view. Were you persuaded by the evidence, the effort you had put in, or the way someone sounded? Name one check you will use before your next pitch.
Sounding sure is not the same as knowing
You can know a business well and still be wrong about its future. You can also be right while sounding unsure.
Start by separating three things: how confident you feel, how accurate your forecast turns out to be, and how narrow a range you give. A confident pitch should make you ask better questions, rather than stop asking them.
Research and nuance
An analyst can overestimate performance, rank themselves too highly against others or use an unjustifiably narrow range. Moore and Healy distinguish these forms of overconfidence. They need not occur together. A confident voice is not a measure of accuracy, and a cautious voice is not automatically well calibrated. Assess the evidence, task and expressed uncertainty rather than label a personality.
Look beyond your favourite story
You know why DailyCup’s next cafe could succeed. What happened when similar businesses opened similar sites? Look for comparable launches, including the ones that struggled.
This comparison group is your reference class. Its base rate gives you a starting point to challenge your story. It will not tell you the answer if the businesses or conditions are materially different.
Research and nuance
Detailed knowledge of one company can make its story compelling. Compare it with a relevant reference class: businesses or projects sharing important features. Inspect selection and differences before applying an average. Base rates can challenge an inside-view forecast, but they do not remove the need to understand context. A poor comparison can be as misleading as no comparison.
Put a number on what you mean
“It will probably work” is difficult to learn from. Try: “I give the new site a 70% chance of reaching the stated sales target by December.” Define the target and the source that will settle it.
A 70% forecast allows a 30% chance of failure. You need a series of forecasts to see whether your confidence is usually well judged.
Research and nuance
Define the event and resolution date before expressing a probability. Across a sufficiently informative set, compare confidence with observed frequencies. A 70% event can fail without the probability being irrational; an event called certain deserves different scrutiny. Small classroom sets illustrate the method, not a stable diagnosis of ability. Retain mistakes as well as successes to avoid selecting the flattering record.
Give a range you can explain
“DailyCup is worth somewhere between nothing and £10 million” covers plenty of possibilities but barely helps a decision. Explain the assumptions behind the low and high values.
Then identify the information that would narrow the range. Your aim is useful honesty about uncertainty. It is not to sound certain, or to make a forecast so vague that you can never be wrong.
Research and nuance
A range so wide that every outcome fits may reveal little. A narrow range with weak support can mislead. Explain what sets the bounds, what is excluded and which evidence would narrow uncertainty. Distinguish a sensitivity range from a probability interval. For investing, calibrated uncertainty should inform research effort and risk discussion rather than become a competition to sound most confident.
A small invented calibration record
Twenty clearly defined fictional forecasts were each assigned 70% confidence before resolution;14 occurred. In a separate five-event illustration, probabilities are .8,.7,.6,.4,.2 and outcomes 1,1,0,1,0. The optional Brier score is mean squared probability error.
- Observed frequency in the first set=14/20=70%.
- That matches the assigned confidence in this small set; it does not establish lasting calibration.
- Optional squared errors=.04,.09,.36,.36,.04; sum=.89.
- Mean Brier score=.89/5=.178; lower is better under this scoring convention, with 0 perfect on the resolved set.
A score on a small artificial set is practice feedback, not a rating of a pupil’s character or future investment skill.
Put it into practice
1. Define an event
Improve “DailyCup will do well” into a forecast with a metric, threshold, period and resolution source.
Write your response in your workbook before opening feedback.
Compare with a model response
For example, a specified outlet’s paid repeat-visit rate exceeds a stated threshold for a defined cohort by a set date, resolved from the reconciled case ledger. Keep the threshold separate from its probability.
2. Use a reference class
A manager predicts every new outlet will beat the mature outlet. What comparison would help?
Write your response in your workbook before opening feedback.
Compare with a model response
Inspect a defined set of comparable launches, including failures and later cohorts, with compatible cost and location conditions. Explain differences and avoid selecting only successful openings.
3. Review a range
A pupil gives £0–£10m for a small café’s value. Is the range automatically excellent because it contains the later estimate?
Write your response in your workbook before opening feedback.
Compare with a model response
Coverage alone is not enough. Explain bounds, evidence and decision usefulness. A narrower justified range can be more informative, but no range should pretend uncertainty has disappeared.
Notice your own judgement
Think about your first view. Were you persuaded by the evidence, the effort you had put in, or the way someone sounded? Name one check you will use before your next pitch.
Original On Judgement teaching. Research and further reading: Likierman; Yale teaching.
Jargon buster
Calibration
The correspondence between stated confidence and observed accuracy over judgements.
Overprecision
Expressing more certainty or a narrower range than evidence supports.
Reference class
A relevant comparison set of similar cases.
Base rate
An observed frequency in a defined comparison group.
Resolution rule
How and when a forecast outcome will be determined.
Brier score
Mean squared probability error for defined binary outcomes.
Knowledge check
Make each choice on the page. Feedback explains the reasoning. Use Try again after revisiting an idea.
AQA connection and further reading
AQA 7138 applied links: AO 2–AO 4 evidence, analysis and evaluation (4.2); uncertainty and change (3.3.4), with quantitative interpretation in Annex 6 where used. Named psychological effects and calibration methods are investing enrichment, not specified AQA content. Classroom exercises illustrate processes; they do not diagnose individual traits.
AQA 7138 specification
Primary curriculum reference; links and original classroom rubrics are interpretive, not endorsement.
Likierman · six elements explained by London Business School
Public LBS explanation checked on 1 November 2026. Six elements are attributed to Sir Andrew Likierman; the three-area grouping and investing exercises are On Judgement adaptations, not his published model or an endorsement.
Andrew Likierman · Judgement at Work: Making Better Choices
Publisher book page. The full book has not been reviewed; teaching uses the publicly explained six-element framework with original examples.
Moore and Healy (2008) · The Trouble With Overconfidence
Author-hosted primary research distinguishes forms of overconfidence. No classroom personality diagnosis or effect-size claim.
Understand yourself as an investor
Where did your confidence come from? Identify a gap in relevant knowledge and one way to compensate for it.
Keep this reflection private unless you choose to share. Use evidence from the fictional exercise; no personal finances or fixed investor-personality label is required.
Take forward
Distinguish confidence, accuracy and precision. Use reference cases and probability statements carefully. Review calibration across a set of judgements.